Yvonne Connolly Martin

Last updated
Yvonne Connolly Martin
Born(1936-09-13)September 13, 1936
NationalityAmerican
Alma mater Carleton College, Northwestern University
SpouseWilliam Brady Martin
Scientific career
FieldsComputational chemistry
Institutions Abbott Laboratories

Yvonne Connolly Martin (born September 13, 1936) is an American cheminformatics and computer-aided drug design expert who rose to the rank of Senior Volwiler Research Fellow at Abbott Laboratories (now AbbVie). Trained in chemistry at Northwestern University, she became a leader in collaborative science aimed at discovering and developing bioactive molecules as therapeutic agents, with her contributions proceeding from application of methods to understand how descriptors of molecular shapes and physicochemical properties relate to their biological activity. [1] She is the author of a seminal volume in cheminformatics, Quantitative Drug Design (2nd Ed., 2010), and has been the recipient of numerous awards in her field, including being named as a fellow of the American Association for the Advancement of Science (1985) and of the International Union of Pure and Applied Chemistry (2000), and receiving the Herman Skolnik Award (2009) [2] and the Award for Computers in Chemical and Pharmaceutical Research (2017) [3] from the American Chemical Society.

Contents

Early life and education

Yvonne Connolly was born to Irene and Elvert Connolly in 1936. [4] [5]

Martin received a bachelor's degree in 1958 from Carleton College, Northfield, Minnesota. She was the only woman to be a chemistry/zoology major in her year. [4] From 1958 to 1960 she worked as a pharmacology assistant at Abbott Labs. She was awarded a predoctoral fellowship from the National Science Foundation for the years 1960–1963, attending Northwestern University, Evanston, Illinois. [4] She received her Ph.D. in physical biochemistry from Northwestern University in 1964. [6]

Career

External videos
Nuvola apps kaboodle.svg "Tautomers: A Rant", Yvonne Martin, 2009, ChemAxon

Martin's career has been almost exclusively with the division of Abbott Laboratories that was involved with preclinical drug discovery initiatives, a division that was spun off from that biomedical conglomerate to become the standalone pharmaceutical company, AbbVie. [2] Martin's career at Abbott and AbbVie extended over forty years, interrupted only a sabbatical year, 1967 to 1968, that she spent working with QSAR pioneer Corwin Hansch at Pomona College, [2] after which she returned to Abbott Laboratories. [4] Martin formally retired as a senior research fellow in 2006, but has continued to be associated with Abbott Laboratories on a contract basis, working on topics in which she is interested. [4] She has also taught as a visiting professor at the University of Virginia. [4]

Research interests

Martin's work with Corwin Hansch led to her ongoing work in QSAR, [7] using computers to develop both 2D and 3D models capturing the chemical and biological properties of molecules. As an early proponent of computational chemistry and its use in drug design, she developed combinatorial chemistry and molecular graphics techniques and was involved in the development of software packages for pharmacophore analysis such as DISCO [8] [9] and ALADDIN. [10] [11] Her work has directly affected modern day drug discovery and supported the computer design of novel compounds. [1] [10] Martin has particularly focused on identifying properties of molecules relevant to biological activity, [4] including their potency, binding affinity, and ADME properties. [1] Her methods have been applied to the study of diseases including hypertension, Parkinson's disease, ulcers, bacterial infections, arthritis, and angina. [4]

She has also significantly contributed to the development of compound collections and combinatorial libraries which investigators can use to develop and compare measures of molecular similarity and diversity. Her collection of MAO (monoamine oxidase) inhibitors has been widely used by researchers. [1]

Other activities

In 1989 Martin helped to found the International Quantitative Structure Activity Relationship & Modeling Society (now called the QSAR, Chemoinformatics and Modeling Society). She served as a board member and was chair of the organization from 2001 to 2005. [4] [2]

Published works

In addition to more than a hundred scholarly publications, she has written or edited six books. [4] These include her textbook on Quantitative Drug Design. [12] Editorially, she has worked on Perspectives in Drug Design and Discovery, QSAR: Annual Reports in Computational Chemistry, Journal of Computer-Aided Drug Design and QSAR & Combinatorial Science. [1] She has registered eight patents. [4] She is listed in the World directory of crystallographers : and of other scientists employing crystallographic methods. [6]

Awards and honors

Personal life

Martin is married to William Brady Martin, a professor of chemistry at Lake Forest College in Lake Forest, Illinois, and has two children. [4] [5]

Related Research Articles

Cheminformatics refers to the use of physical chemistry theory with computer and information science techniques—so called "in silico" techniques—in application to a range of descriptive and prescriptive problems in the field of chemistry, including in its applications to biology and related molecular fields. Such in silico techniques are used, for example, by pharmaceutical companies and in academic settings to aid and inform the process of drug discovery, for instance in the design of well-defined combinatorial libraries of synthetic compounds, or to assist in structure-based drug design. The methods can also be used in chemical and allied industries, and such fields as environmental science and pharmacology, where chemical processes are involved or studied.

<span class="mw-page-title-main">Drug design</span> Invention of new medications based on knowledge of a biological target

Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals including peptides and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.

In the physical sciences, a partition coefficient (P) or distribution coefficient (D) is the ratio of concentrations of a compound in a mixture of two immiscible solvents at equilibrium. This ratio is therefore a comparison of the solubilities of the solute in these two liquids. The partition coefficient generally refers to the concentration ratio of un-ionized species of compound, whereas the distribution coefficient refers to the concentration ratio of all species of the compound.

Quantitative structure–activity relationship models are regression or classification models used in the chemical and biological sciences and engineering. Like other regression models, QSAR regression models relate a set of "predictor" variables (X) to the potency of the response variable (Y), while classification QSAR models relate the predictor variables to a categorical value of the response variable.

<span class="mw-page-title-main">Medicinal chemistry</span> Scientific branch of chemistry

Medicinal or pharmaceutical chemistry is a scientific discipline at the intersection of chemistry and pharmacy involved with designing and developing pharmaceutical drugs. Medicinal chemistry involves the identification, synthesis and development of new chemical entities suitable for therapeutic use. It also includes the study of existing drugs, their biological properties, and their quantitative structure-activity relationships (QSAR).

<span class="mw-page-title-main">Pharmacophore</span> Abstract description of molecular features

In medicinal chemistry and molecular biology, a pharmacophore is an abstract description of molecular features that are necessary for molecular recognition of a ligand by a biological macromolecule. IUPAC defines a pharmacophore to be "an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger its biological response". A pharmacophore model explains how structurally diverse ligands can bind to a common receptor site. Furthermore, pharmacophore models can be used to identify through de novo design or virtual screening novel ligands that will bind to the same receptor.

Corwin Herman Hansch was a professor of chemistry at Pomona College in California. He became known as the 'father of computer-assisted molecule design.'

The structure–activity relationship (SAR) is the relationship between the chemical structure of a molecule and its biological activity. This idea was first presented by Crum-Brown and Fraser in 1865. The analysis of SAR enables the determination of the chemical group responsible for evoking a target biological effect in the organism. This allows modification of the effect or the potency of a bioactive compound by changing its chemical structure. Medicinal chemists use the techniques of chemical synthesis to insert new chemical groups into the biomedical compound and test the modifications for their biological effects.

This page describes mining for molecules. Since molecules may be represented by molecular graphs this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics.

<span class="mw-page-title-main">Chemical Computing Group</span> Software company in Canada

Chemical Computing Group is a software company specializing in research software for computational chemistry, bioinformatics, cheminformatics, docking, pharmacophore searching and molecular simulation. The company's main customer base consists of pharmaceutical and biotechnology companies, as well as academic research groups. It is a private company that was founded in 1994; it is based in Montreal, Quebec, Canada. Its main product, Molecular Operating Environment (MOE), is written in a self-contained programming system, the Scientific Vector Language (SVL).

<span class="mw-page-title-main">Chemical similarity</span> Chemical term

Chemical similarity refers to the similarity of chemical elements, molecules or chemical compounds with respect to either structural or functional qualities, i.e. the effect that the chemical compound has on reaction partners in inorganic or biological settings. Biological effects and thus also similarity of effects are usually quantified using the biological activity of a compound. In general terms, function can be related to the chemical activity of compounds.

Molecular design software is notable software for molecular modeling, that provides special support for developing molecular models de novo.

Peter Willett is an Emeritus Professor of Information Science at the University of Sheffield, England.

<span class="mw-page-title-main">Sean Ekins</span>

Sean Ekins is a British pharmacologist and expert in the fields of ADME/Tox, computational toxicology and cheminformatics at Collaborations in Chemistry, a division of corporate communications firm Collaborations in Communications. He is also the editor of four books and a book series for John Wiley & Sons.

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Molecular Operating Environment (MOE) is a drug discovery software platform that integrates visualization, modeling and simulations, as well as methodology development, in one package. MOE scientific applications are used by biologists, medicinal chemists and computational chemists in pharmaceutical, biotechnology and academic research. MOE runs on Windows, Linux, Unix, and macOS. Main application areas in MOE include structure-based design, fragment-based design, ligand-based design, pharmacophore discovery, medicinal chemistry applications, biologics applications, structural biology and bioinformatics, protein and antibody modeling, molecular modeling and simulations, virtual screening, cheminformatics & QSAR. The Scientific Vector Language (SVL) is the built-in command, scripting and application development language of MOE.

<span class="mw-page-title-main">Johann Gasteiger</span> German chemist (born 1941)

Johann Gasteiger is a German Chemist and a Chemoinformatician on which he wrote and edited various books.

Cynthia Rachel D. Selassie is an American bio-organic and medicinal chemist known for her work with quantitative structure-activity relationships (QSAR). She is the Blanche and Frank R. Seaver Professor of Science and professor of chemistry at Pomona College in Claremont, California.

Andrea Volkamer is a German bioinformatician and professor of “Data-Driven Drug Design” at Saarland University and an associated researcher at the Helmholtz Institute for Pharmaceutical Research Saarland (HIPS). Her research focuses on data-driven drug design, with an emphasis on method development and application.

<span class="mw-page-title-main">Jordi Mestres i López</span> Catalan chemical researcher and genealogist (b. 1967)

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References

  1. 1 2 3 4 5 6 "2005 SBS Accomplishment award to Martin". The Cheminformatics and QSAR Society. 14 October 2005. Retrieved 27 January 2016.
  2. 1 2 3 4 5 Goethe G. "2009 Herman Skolnik Award Winner Announced". American Chemical Society. Retrieved 27 January 2016.
  3. 1 2 "ACS Award for Computers in Chemical & Pharmaceutical Research: Yvonne C. Martin". C&EN Global Enterprise. 95 (1): 45–50. 2017-01-02. doi:10.1021/cen-09501-awards037.
  4. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Gardner C. "2013 Alumni Association Award Recipients". Carleton Alumni Network. Retrieved 27 January 2016.
  5. 1 2 "Yvonne Connolly Martin '58 and her husband Bill find seats during Friday's Heywood Society Luncheon". Carleton Alumni Network. Retrieved 27 January 2016.
  6. 1 2 Epelboin Y (1995). World directory of crystallographers and of other scientists employing crystallographic methods (9th ed.). Dordrecht: Kluwer Academic. p. 235. ISBN   978-0-7923-3180-3.
  7. Martin YC (May 2012). "Hansch analysis 50 years on". Wiley Interdisciplinary Reviews: Computational Molecular Science. 2 (3): 435–442. doi:10.1002/wcms.1096. S2CID   96662838.
  8. Merz KM, Ringe D, Reynolds CH (2010). Drug design : structure- and ligand-based approaches (1st ed.). Cambridge [U.K.]: Cambridge University Press. p. 138. ISBN   978-0-521-88723-6.
  9. Güner OF (1999). Pharmacophore perception, development, and use in drug design. LaJolla, CA: International University Line. pp. 16, 49–68. ISBN   978-0-9636817-6-8.
  10. 1 2 3 "Honorary Members of the MGMS Community". Molecular Graphics and Modelling Society. Retrieved 27 January 2016.
  11. Van Drie JH, Weininger D, Martin YC (1989). "ALADDIN: an integrated tool for computer-assisted molecular design and pharmacophore recognition from geometric, steric, and substructure searching of three-dimensional molecular structures". Journal of Computer-aided Molecular Design. 3 (3): 225–51. doi:10.1007/BF01533070. PMID   2573695. S2CID   206795998.
  12. Martin YC (2010). Quantitative drug design : a critical introduction (2nd ed.). Boca Raton: CRC Press/Taylor & Francis. ISBN   978-1-4200-7099-6.
  13. Stouch TR (11 December 2009). "A well deserved honor: Yvonne Martin, 2009 recipient of the Herman Skolnik Award". Journal of Computer-Aided Molecular Design. 23 (12): 829–830. Bibcode:2009JCAMD..23..829S. doi: 10.1007/s10822-009-9311-2 . PMID   20012465 . Retrieved 27 January 2016.